Today, accurate weather forecasting relies on a detailed understanding of the science of the weather, developing very complex computer models to represent this science and using as much accurate data as possible to ensure a robust outcome. The greater the volume of accurate input data, the higher the likelihood of producing a robust and successful forecast. To put into context exactly how much data is required, it has been estimated that the Met Office in Exeter processes as much data as the entire UK financial sector on a daily basis. In order to achieve this mammoth task, huge amounts of computing power are brought to bear. The Met Office’s current IBM supercomputer can do more than 1000 trillion calculations a second which is equivalent to more than 100,000 home PCs.

How is it possible to model such a complex system?
The Met Office models the atmosphere by breaking it down into two main areas: the dynamics which describe the large scale motions and the physics which define the more local processes or physical processes like cloud formation, the interaction of light with parts of the atmosphere and then the constituents of the atmosphere including rainfall. The model is undergoing constant improvement and enhancement to deliver more accurate forecasts. The dynamical core, which is the part of the model that solves the equations of motion of the atmosphere, was upgraded in July 2014 as the result of a ten year project that has come to fruition.

Despite the huge amount of computing power currently available to the Met Office, there is always an appetite for more, knowing that processing power is a limiting factor. With a major investment in a next generation supercomputer already agreed and with hardware under development, it has been possible to plan how best to develop the forecast models to make the most effective use of the available technology.

One key area is improving the resolution of the models. Currently the global models have horizontal grid spacing of about 17km, and our UK models have a grid spacing of 1.5km. In the vertical, the model simulates the atmosphere by breaking it down into between 50 and 100 layers. The smaller the grid spacing and the thinner the layers, the more accurate the model will be: The trade-off is the increased time it takes to run the model.

Another major development that additional computing power will allow is moving away from modelling the sea as having a fixed surface temperature to having a more complete scenario that also includes an accurate model of the ocean. Climate research has required accurate models of the oceans for over twenty years, but for weather forecasting this has been too complex until now. This type of enhanced model would come into its own when forecasting tropical cyclones, hurricanes and typhoons, where the interaction between the atmosphere and the ocean is fundamental.

Another way that increased computing power will help improve accuracy is through ensemble forecasts. Rather than running just a single forecast, it is possible to run multiple forecasts at the same time with slightly different parameters and interpret the output from them probabilistically using statistical analysis. More computing power will allow both more forecasts within each ensemble and more sophisticated methods for their initialisation.

Modelling climate change
The Met Office also uses its models to assess climate change, where there is a drive to improve the complexity of the simulations still further. The levels of complexity required for climate projections tend to be higher than those that are included in a weather model as processes that may have a small impact on short timescales can have important feedbacks on the longer-term evolution of the climate. This means that as well as using the atmospheric and land surface models used for weather forecasting and the ocean components discussed above, long-term climate models now include factors such as chemistry and biogeochemistry, which is the interaction of biology with the environment. A new flagship earth system model called UKESM1, which is a collaborative programme between the Met Office and UK academia is currently under development and will be launched in the next couple of years.

Dr David Walters

David is the Scientific Manager of the Global Atmospheric Model Development team at the Met Office and manages research to maintain and develop the global atmosphere configurations of the unified model. David and his team work in collaboration with scientists covering multiple meteorological disciplines to pull through new scientific developments and improvements to the Met Office’s global atmospheric model. They assess model performance across different timescales and its sensitivity to both new model formulations and uncertainties in physical parametrizations and numerical formulation.